An Arbitrarily Reconfigurable Extreme Learning Machine Inference Engine for Robust ECG Anomaly Detection-Reference-Cited by-同舟云学术

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An Arbitrarily Reconfigurable Extreme Learning Machine Inference Engine for Robust ECG Anomaly Detection

Published:2021 Issue: Volume:2 Page:196-209
ISSN:2644-1225
Container-title:IEEE Open Journal of Circuits and Systems
language:
Short-container-title:IEEE Open J. Circuits Syst.

Author:

Chuang Yu-Chuan^ORCID,Chen Yi-Ta^ORCID,Li Huai-Ting,Wu An-Yeu Andy^ORCID

Funder

Ministry of Science and Technology of Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Medicine

Link

http://xplorestaging.ieee.org/ielx7/8784029/9314963/09335310.pdf?arnumber=9335310

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Object classification through heterogeneous fog with a fast data-driven algorithm using a low-cost single-photon avalanche diode array;Optics Express;2024-09-03

2. A Novel Instruction Driven 1-D CNN Processor for ECG Classification;Sensors;2024-07-05

3. An Energy-Efficient Configurable Coprocessor Based on 1-D CNN for ECG Anomaly Detection;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

4. An Ultra-Lightweight Time Period CNN Based Model with AI Accelerator Design for Arrhythmia Classification;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

5. An Energy-Efficient ECG Processor Based on HDWT and a Hybrid Classifier for Arrhythmia Detection;Applied Sciences;2023-12-29

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